Systems and Methods of Adaptive Beamforming for Mobile Satellite Systems Based on User Locations and Co-Channel Waveforms

ABSTRACT

Systems and methods for adaptive beamforming for a mobile satellite system (MSS). Embodiments described herein provide individual-user-optimized, adaptive beamforming. One example system creates a user beam optimized based either on known user locations or the waveforms received from all cochannel users. The user beam maximizes the signal-to-interference-noise relative to the desired user, both in the forward and return links. The optimization process considers the spatial distribution of all cochannel users in the footprint of the satellite. The user beam adapts to the user&#39;s location and co-channel interference environment.

RELATED APPLICATIONS

The present application is a continuation of U.S. application Ser. No.16/796,322, filed on Feb. 20, 2020, which is related to and claimsbenefit under 35 U.S.C. § 119(e) from U.S. Provisional PatentApplication Ser. No. 62/808,698, filed Feb. 21, 2019, titled “Systemsand Methods of Adaptive Beamforming for Mobile Satellite Systems Basedon User Location/Waveform,” the disclosures of which are incorporatedherein by reference in their entirety and to which priority is claimed.

FIELD

Embodiments described herein relate to satellite and terrestrialwireless communications systems and, more particularly, to interferencereduction through adaptive beamforming in satellite communicationssystems.

SUMMARY

Satellites used in modern mobile satellite systems (MSS), andterrestrial cellular base station antennas use multiple antenna feedelements to form a plurality of service areas (or cells). Conventionalbeamformers form fixed, regional spot beams for MSS, or sector beams forcellular systems. In general, spot beams and/or sector beams canincrease the network capacity by enabling frequency reuse among the spotbeams; the same applies to terrestrial sector beams. The regional spotbeam or sector beam is usually shared by many users inside the beam, butusers near the edge of the beam may have disadvantages such as gain andpower degradation and adjacent cochannel beam interference. As the beammust cover many users, who may occupy a wide frequency band—the beam'sbandwidth is made wide—even though each individual user may use arelatively narrowband subband. This unnecessarily compromises thebeamformer's degrees of freedom to optimize the performance of eachindividual user. Besides, the fixed regional spot beam or sector beam isnot adaptive to the users' individual operating conditions, such as:usage of power and bandwidth, and received interference power(intra-system and extra-system) as functions of time and user location.The above (and other) limitations of conventional beamforming systemsare addressed in the present disclosure.

Examples of adaptive space-time signal processing comprisinginterference suppression and multi-user detection in a CDMA mobilesatellite system environment are described in U.S. Pat. No. 7,813,700 B2(“Adaptive beam forming with multi-user detection and interferencereduction in satellite communication systems”). Embodiments presentedherein provide systems and methods of adaptive beamforming, whichinvolve more general waveforms, such as FDMA/TDMA/OFDMA, found in modern4G/5G cellular systems. The systems and methods are applied to both thereturn and forward links.

Such embodiments are based on knowledge of the user's location. In oneembodiment, this knowledge may be provided by the user equipment (UE),which may be equipped with a navigation subsystem, such as GPS, andthereby be aware of its own location. The user location information maybe transferred from the UE to the S-BSS (Satellite Base StationSubsystem) by the air interface.

In another embodiment, applicable to the return link, the location ofthe user (which is the same as and, in this application, usedinterchangeably with UE location) may be estimated at the S-BSS from thespatial signature of return link transmissions and knowledge of thereturn signal waveform. Here, “spatial signature” refers to thedistribution of the received power as a function of the Angle of Arrival(AoA) of the return link signal. In both embodiments, a customized,virtual beam is formed inside the S-BSS for each individual user, whichmaximizes the received signal-to-interference-and-noise power ratio forthe particular user, considering the actual, spatial distribution of allcochannel users (i.e., the users sharing the same frequency in differentbeams). This customized virtual beam is referred to as a user beam, asmentioned above. The beam is referred to as “virtual” as it formed bysignal processing software in the beamformer, although it performsexactly the same function as traditional, “real” beams formed byphysical components such as phase shifters, amplifiers, and attenuators.Hereafter, the qualifier, “virtual,” is dropped when referring to thebeams of the present system.

The above-described principle may also be applied in the forward link asfollows. An embodiment using frequency division duplexing (FDD) isdescribed first. Given explicit knowledge of the UEs' locations at theS-BSS, which may be transported from the UEs to the S-BSS via the returnlink as indicated above, the S-BSS can form a user beam using knowledgeof the RF calibration of the satellite's antenna subsystem, or feedelements. This calibration enables the S-BSS to determine the complexweights that should be applied to each feed element in order to achievethe objective spatial signature, or transmit gain pattern, necessary toform user beams for each UE. This transmit gain pattern would beoptimized to jointly maximize the gain towards the targeted (i.e.desired) UE while minimizing the gains towards all UEs that arespatially well separated from the targeted UE and reusing the samefrequency.

In another embodiment, time division duplexing (TDD) using a commonreturn and forward link frequency may be used. In this embodiment, inaddition to using explicit, a priori knowledge of the UE locations togenerate the beamforming weights, the S-BSS may be able to substantiallyreuse the weights derived from return link optimization.

In addition to enabling optimization of the forward-downlink user beam,real time knowledge of the UE locations also enables the satellite'spower to be dedicated exclusively to the active users—i.e., to directpower to geographic locations where it is needed. Many traditional MSSnetworks blanket the entire footprint of the satellite with uniformpower, as the actual locations of the users are unknown, but they mayappear unpredictably anywhere in the footprint. It has been found that,in most MSS networks, the service demand density is highly non-uniformover the footprint of the satellite. This leads to considerable waste ofsatellite power when it is distributed uniformly over geography. It isnoteworthy that downlink power and bandwidth are key, finite resourcesin an MSS network.

The following discussion applies to both the forward and return links.The adaptive user beam is formed with a bandwidth that corresponds tothe user's signal bandwidth (BW), also referred to as the nominalchannel bandwidth. This bandwidth may vary between the users. Matchingbeamforming BW to the user's signal BW maximizes the beamformer'sdegrees of freedom to optimize the performance of each individual user.The user beam pattern is adaptive to the user's location and thecochannel interference environment. Note that, unlike an RF or IFimplementation, which is common in many traditional systems, beamformingwith the user's signal bandwidth is relatively easy to implement whenperformed as a part of the received signal demodulation process, as itis in the embodiments presented herein.

The reason for the above simplification is as follows. When a user'schannel bandwidth is sufficiently small that the differential frequencyresponses of the feed element paths over the said bandwidth is flat,i.e. the gains and phase shifts are frequency independent, thebeamforming can be classified as “narrowband”. Narrowband beamformingcan be performed with relatively simple, frequency independent, scalarmultipliers; in contrast, wideband beamforming requires frequencydependent, vector multipliers, i.e. transversal filters. Alternatively,the feed element paths may first have their frequency responsesequalized over the beam's bandwidth, after which scalar multipliers canbe used. Either approach imposes a substantial burden on traditionalsatellite networks, especially for ground based beamforming (GBBF),compared to the requirements of the present system.

BRIEF DESCRIPTION OF THE DRAWINGS

The accompanying figures, where like reference numerals refer toidentical or functionally similar elements throughout the separateviews, together with the detailed description below, are incorporated inand form part of the specification, and serve to further illustrateembodiments of concepts that include the claimed invention, and explainvarious principles and advantages of those embodiments.

FIG. 1A is a diagram of an adaptive beamforming system according to someembodiments.

FIG. 1B illustrates ground-based beamforming systems according to someembodiments.

FIG. 2 illustrates a plurality of spot beam zones.

FIG. 3 illustrates aspects of the operation of the adaptive beamformingsystem of FIG. 1 according to some embodiments.

FIG. 4 is a flow diagram of a resource allocation procedure, accordingto some embodiments.

FIG. 5 illustrates an example of how a user beam is formed according tosome embodiments.

FIG. 6 illustrates a spot beam formed by prior art systems.

FIG. 7 illustrates aspects of the operation of the adaptive beamformingsystem of FIG. 1 according to some embodiments.

FIG. 8 illustrates an example of return link (RL) beam contours producedwith the adaptive beamforming system of FIG. 1 according to someembodiments.

FIG. 9 illustrates an example of return link (RL) beam contours with aprior art beamforming system.

FIG. 10 is a chart illustrating the performance of the adaptivebeamforming system of FIG. 1 according to some embodiments.

FIG. 11 is a chart illustrating the performance of the adaptivebeamforming system of FIG. 1 according to some embodiments.

FIG. 12 illustrates aspects of the operation of the adaptive beamformingsystem of FIG. 1 according to some embodiments.

FIG. 13 is flow diagram illustrating an adaptive user beam startupprocedure, according to some embodiments.

FIG. 14 illustrates an adaptive beamforming system according to someembodiments.

FIG. 15 is a chart illustrating performance improvements of a user beamsystem over a conventional fixed spot beam system according to someembodiments.

Skilled artisans will appreciate that elements in the figures areillustrated for simplicity and clarity and have not necessarily beendrawn to scale. For example, the dimensions of some of the elements inthe figures may be exaggerated relative to other elements to help toimprove understanding of embodiments of the present invention.

The apparatus and method components have been represented whereappropriate by conventional symbols in the drawings, showing only thosespecific details that are pertinent to understanding the embodiments ofthe present invention so as not to obscure the disclosure with detailsthat will be readily apparent to those of ordinary skill in the arthaving the benefit of the description herein.

DETAILED DESCRIPTION

Before any embodiments are explained in detail, it is to be understoodthat the disclosure is not limited in its application to the details ofconstruction and the arrangement of components set forth in thefollowing description or illustrated in the following drawings. Thedisclosure is capable of other embodiments and of being practiced or ofbeing carried out in various ways.

It should also be noted that a plurality of hardware and software baseddevices, as well as a plurality of different structural components maybe used to implement aspects of the disclosure. In addition, it shouldbe understood that embodiments may include hardware, software, andelectronic components or modules that, for purposes of discussion, maybe illustrated and described as if the majority of the components wereimplemented solely in hardware. However, one of ordinary skill in theart, and based on a reading of this detailed description, wouldrecognize that, in at least one embodiment, the electronics-basedaspects may be implemented in software (e.g., stored on non-transitorycomputer-readable medium) executable by one or more electronicprocessors (for example, microprocessors). As such, it should be notedthat a plurality of hardware and software based devices, as well as aplurality of different structural components may be utilized toimplement the disclosure. For example, “control units” and “controllers”described in the specification can include one or more processors, oneor more memory modules including non-transitory computer-readablemedium, one or more input/output interfaces, and various connections(e.g., a system bus) connecting the components.

For ease of description, the example systems or devices presented hereinmay be illustrated with a single exemplar of each of its componentparts. Some examples may not describe or illustrate all components ofthe systems. Other example embodiments may include more or fewer of eachof the illustrated components, may combine some components, or mayinclude additional or alternative components.

Embodiments described herein provide individual-user-optimized, adaptivebeamforming for mobile satellite systems. One example system creates a‘beam for each user’, referred to as ‘user beam’ (that is, forcommunication with user equipment participating in the mobile satellitesystem). As used herein, the term “user equipment” or “UE” includessatellite radiotelephones or data terminals, including smart telephonesand access points for internet of things (IoT), wherein the terminalincludes a radio frequency transceiver and may also include a globalpositioning system (GPS) or global navigation satellite system (GNSS)receiver. The user beam is optimized based either on known userlocations or the attributes, or signatures, of waveforms received fromall cochannel users. The system operates in an environment ofsignificant frequency reuse among the cochannel users. Knowledge of userlocations is transferred to the S-BSS (Satellite Base Station Subsystem)by the return link or is derived at the S-BSS from estimation of thespatial signature of the return link signals with knowledge of pilotsignals in the return link waveform. The user beam maximizes thesignal-to-interference-noise relative to the desired user, both in theforward and return links. The optimization process considers the spatialdistribution of all cochannel users in the footprint of the satellite.The user beam adapts to the user's location and co-channel interferenceenvironment. By simulation, the performance of the beamforming system iscompared with an existing fixed beamforming system, represented by amajor GEO MSS covering the Continental United States and Canada. Thesimulation results show that user-optimized adaptive beamforming offerssignificant capacity advantages over the legacy beamforming, measured byaggregate system throughput.

1. New User Beamforming System and Adaptive Resource Scheduler

FIG. 1A illustrates a high-level block diagram of an adaptivebeamforming system 100. The described methods may be applied to bothcellular networks and MSS, although the present narrative treats thelatter as the preferred embodiment for the purpose of explaining theconcepts. Within the MSS category are included both on-boardbeamforming, wherein the beams are formed on the satellite, and groundbased beamforming (GBBF), where the beams are formed by subsystems of asatellite earth station, or gateway. The system block diagram of FIG. 1Aapplies, in a general way, to all the above embodiments.

The following are the major elements, or subsystems, of the beamformersystem 100.

Antenna array 102: A fundamental component in a beamformer is an arrayof multiple antennas. The antennas and their feeder electronics (whichfeed radio signals to and from the antenna elements) are often referredto as feed elements.

Channelizer 104: This subsystem subdivides a broad operating RF band,for example, the MSS L-band, into sub-bands that may be more suitable asoperating channel bandwidths, transmit power amplifiers, and receive lownoise amplifiers. Channelizers are more common in satellite systems andmay not be necessary in cellular systems operating with lower RFbandwidths relative to the operating frequency.

RF/IF 106: This represents analog electronics that may exist between theantenna array and the Satellite Base Station Subsystem (S-BSS). Theseelectronics may be distributed between the satellite and the groundbased gateway in satellite embodiments, or the tower head and radioaccess network (RAN) equipment in terrestrial cellular embodiments.

Satellite Base Station Subsystem (S-BSS) 108: This performs the RANfunctions of resource scheduling and data/signal processing required bythe lower layers of the protocol stack. The following explains somedifferences between how beamforming is performed in existing systems andhow it is performed in the embodiments discussed herein.

Traditional beamforming architecture: For transmit operation, a datastream from an upper layer of the communication protocol stack isconverted into a single stream of transmit symbols. These symbols arefed to a beamformer, which may be analog or digital in implementation.The beamformer converts the single stream into M symbol-streams withappropriate relative amplitudes and phases. The said M streams are thenfed to an M-element antenna array. For receive operation, thetraditional beamformer linearly combines the M received symbol streamsinto a single stream. The combining process applies appropriateamplitude weights and phase shifts to each stream. The said singlestream is then provided to the S-BSS for receive-mode signal/dataprocessing corresponding to the lower layers of the communicationsprotocol stack. The above operation is performed for every beam of thenetwork.

New Adaptive Beamformer 110: M symbol streams are passed transparently(i.e., preserving the relative amplitudes and phases of the streams, andwith minimal signal distortion) to the S-BSS, as shown in FIG. 1A. Theexample system illustrated in FIG. 1A includes an I/Q (in-phase andquadrature) interface for use with signals' center frequencies, whichare at complex baseband. However, a bandpass IF interface may also beused without departing from the teachings of the present disclosure.

Receive Mode Operation: In the receive mode of operation, the S-BSSreceives an M-element symbol stream (i.e. a stream of complex vectors),instead of a single (i.e. scalar) symbol stream. The linear signalprocessing methods described here may be used to adaptively combine theM-streams into a single stream with an improvedsignal-to-interference-plus-noise ratio (SINR). However, because the newarchitecture makes available to the S-BSS a vector of received symbols,as opposed to a post-beamformed scalar stream, which would be providedif traditional beamforming had been used, the S-BSS is able to applypowerful techniques using vector inputs, including non-lineartechniques, to demodulate the symbols with greater reliability. Examplesof non-linear techniques are Decision Feedback and Multiuser Detection.

Transmit Mode Operation: In the transmit mode, the S-BSS performs thefunction of the beamformer by producing a vector stream instead ofscalar stream. The transmit vector incorporates the appropriate relativeamplitude weights and phase shifts necessary to create the desiredbeams.

The Receive and Transmit mode beamforming operations described above areperformed individually for each UE; hence the beam pattern is customizedto the requirements and operating environment of each UE. It may benoted that, in traditional beamforming, it is one beam for many UEs; allUEs in a beam share the spatial attributes of that beam.

Adaptive Resource Scheduler (ARS) 112: A RAN resource scheduler is acommon subsystem in existing S-BSS's but is usually very loosely coupledto the RAN. In other words, it is typically not responsive to the radiofrequency characteristics of the signals received by the RAN. In the newarchitecture, the resource scheduler is tightly coupled to the RAN,i.e., it is an essential contributor to the adaptivity of thebeamforming system. For example, the adaptive resource scheduler (ARS)determines an optimal frequency, time and power allocation for eachindividual user dynamically, based on the spatial distribution of allactive users and their demands, which may be driven by traffic loads andQuality of Service (QOS) requirements.

FIG. 1B is a block diagram of a system where the beamformer is locatedon the ground, which is the architecture (including both old and newembodiments) corresponding to a ground-based beamformer (GBBF). In theold GBBF architecture 120, the beamformer is separate from the SatelliteBase Station Subsystem (S-BSS) 108, as is the current practice, whereasin the new GBBF architecture 122, the beamforming is integrated in theS-BSS 108.

FIG. 14 illustrates an example beamforming system 1400 whereby anexisting, separately beamforming GBBF 1402, depicted in the oldarchitecture of FIG. 1A, can be logically bypassed in order to connectthe feed element signals directly to the S-BSS. The new adaptivebeamformer 1404 may be added to the existing GBBF as additionalcapability, while preserving the existing GBBF's traditional ability toform beams before the signals are fed to the S-BSS. Note that, in thenew adaptive beamformer, the S-BSS includes the beamformingfunctionality, as in current terrestrial 3GPP systems. According to thenew architecture, the existing GBBF's weights are designed totransparently connect the feed element signals to the S-BSS inputs—onefeed element to one input. These GBBF weights comprise complex vectorswhere one element is set to unity (i.e., 1+j0) and all other elementsare set to zero; the weight element set to unity depends on theparticular feed element that is connected to the S-BSS. The advantage ofthis architecture is that existing S-BSS units can continue to be servedby the existing GBBF operating in its traditional modes, while the newS-BSS can access the feed elements through the existing GBBF operatingin the pass-through mode. This architecture can be applied to bothreturn link beamforming and forward link beamforming.

The motivation for the bypassing of the existing GBBF, described above,may be a commercially desire to preserve the present functions of alegacy GBBF with minimal disruption, while adding the methods of thepresent disclosure as added beamforming options and implementing themexternally (relative to the existing GBBF) in the S-BSS. It should beobvious that, in an alternative embodiment, especially in a newimplementation, the new methods may also be implemented in a standaloneGBBF, with the S-BSS performing its traditional, exclusively RANfunctions. The motivation for this architectural choice may becommercial rather than technical. Because of the close coupling betweenelements of the RAN processing, such as the Adaptive RAN Scheduler, andbeamforming, the technically optimum architecture appears to be a jointRAN Processor and Beamformer, shown as S-BSS in FIG. 14, wherein theseparate GBBF is either eliminated or bypassed, and the feed elementsignals are connected directly to the S-BSS.

A new concept, the “beam zone,” distinct from operational spotbeams, isintroduced in the new system. Beam zones are traditional, fixed(non-adaptive) spotbeams with an N-color reuse. For example, FIG. 2illustrates a plurality of beam zones 202 with the case of N=3 shown asan example, although N may have any value. The beam zones 202 are usedfor frequency planning—they do not represent operational beams. FIG. 3illustrates how the frequency and power allocation are performed by thesystem 100. Assume that a channel bandwidth, B, is available for the newsystem and, to enable 3-color frequency reuse, the band is divided into3 segments, each having a bandwidth of B/3. Each beam zone is allocatedspectrum corresponding to one of the 3-color segments. Users located ina common beam-zone would share the same B/3 spectrum through amultiplexing scheme such as frequency division multiplexing (FDM). Othermultiplexing schemes for sharing a band among multiple users couldequally be used—the use of FDM in the present disclosure should be seenas exemplary rather than essential to the core teachings aboutbeamforming. For example, orthogonal frequency division multiplexing,time division multiplexing, and code division multiplexing may be used.Note that, typically, the beam zones may be too small to allowseparation of the users' signals via beamforming, i.e., spatialmultiplexing. This is owing to the limited aperture of the satellite'santenna array. As in traditional, fixed beam design, the beam zones aredesigned such that cochannel users in adjacent beam-zones have a minimumspatial isolation. Typically, the fixed beam design would incorporatepattern nulls at a number of control points in the adjacent cochannelbeams.

An example frequency allocation scheme 302 is illustrated in the FIG. 3.As an example of using FDM for K users inside a beam-zone, the frequencybandwidth B/3 would be equally divided among the users with each havingB/(3*K)—unequal distributions of bandwidth to users could also be usedwithout departing from the present teachings. This implies that if therewere fewer users inside the beam-zone, the user(s) could occupy morebandwidth than if there were more users inside the same beam. Theadditional bandwidth might be used to provide more throughput to theusers to improve their Quality of Service (QOS) or, alternatively,enable the users to spread their spectrum beyond the minimum requiredfor a targeted QOS, thereby using spread spectrum processing gain toreduce the interference to other cochannel users. As user locations anddistributions change over the time, the frequency allocation dynamicallyadapts to the user situation accordingly.

An example resource allocation procedure 400 is summarized in theflowchart shown in FIG. 4. It starts with the input definition of“beam-zone” location, shape and size (at block 402), and frequency reuseratio N among those “beam-zones” (at block 404), which determines the“beam-zone” layout in coverage area (at block 406). Then, based on theusers' location and distribution (at block 408), the scheduleridentifies users inside each “beam-zone” (at block 410). Assuming thatthe total available bandwidth is B (at block 412) and that there are Kusers in a “beam-zone,” the scheduler assigns B (N*K) BW for each userinside the “beam-zone” (at block 414).

In some embodiments, the users inside a “beam-zone” may use all the B Nfrequency bandwidth through TDMA by allocating an exclusive time slotfor each of the users. In some embodiments, the users may share the B Nfrequency bandwidth through combination of FDM/TDM such as in OFDMAsystem. In some embodiments, the users may share the B/N frequencybandwidth through CDMA, noting that if CDMA were used, a frequency reusecorresponding to N=1 may be feasible.

In distribution of the total EIRP in the forward link, in someembodiments, the adaptive resource scheduler may uniformly distributetransmit power among all active users. This means that satellite poweris distributed proportionally to users' geographic density.

Considering the return link, in some embodiments, different users may beallocated different amounts of transmit power, proportional to their QOSneeds, which may be established by a QOS negotiation with an entity inthe network infrastructure (S-BSS or other entity). The unequaldistribution allows different UE types to be supported in the samebeam-zone.

The following applies to both forward and return link beamforming. Onceresource allocations are done, a customized beam is formed for eachindividual user with beam shape adaptive to cochannel UE distribution.The user beam can be formed with BF algorithm such as adaptive minimummean square error (MMSE) based on user locations or user reference pilotsignals. The pattern generation rule includes maximizing SINR toward thedesired user with consideration of the actual, spatial distribution ofall cochannel users, and each user gets a custom beam. With the methodsdescribed above, the adaptive beamformer is able to optimally utilizedegrees of freedom offered by the antenna feed element array. FIG. 5illustrates an example of how a user beam 500 is formed in principleunder the illustrated user distribution scenario. In a conventionalsystem, illustrated in FIG. 6, a fixed regional spot beam 600 is formedfor all users in the main beam 602. The fixed spot beam 600 usuallyminimizes total received interference plus noise (I+N), subject tospecified gain constraints for main beam 602 and locations ofhypothetical users in cochannel-adjacent beams 604, as illustrated inFIG. 6. In contrast, as shown in FIG. 5, the customized user beam 500maximizes SINR toward the desired user, adaptive to the actual, spatialdistribution of all cochannel users. The fixed beam 600 of FIG. 6 wouldhave disadvantages relative to the adaptive beam (user beam 500), suchas gain degradation and adjacent cochannel beam interference for thoseusers that are near the beam edge. The fixed beam 600 of FIG. 6 alsodedicates the beamformer's degrees of freedom to optimize the beam shapefor hypothetical desired and undesired users, which may not representactual user distributions or actual interference environment.

2. Adaptive Beamforming Methods Based on User Location or Waveform

A customized beam is formed for each individual user with beam shapeadaptive to cochannel UE distribution, informed by the ARS. The adaptiveuser beamforming methods for both return link and forward link aredescribed respectively in this section.

2.1 Return Link Method

Assume that a satellite (not shown) has a 2-D antenna array 702 of Mfeed element elements (see FIG. 7). The m^(th) feed element 704 has thecomplex (gain and phase) response of a_(m) (θ_(k), φ_(k)) at azimuthangle θ_(k) and elevation angle of φ_(k) from the satellite point ofview for the k^(th) user location 706, as illustrated in FIG. 7. Thearray steering vector at the k^(th) user location 706 is thereforedefined by

a(θ_(k),φ_(k))=[a ₁(θ_(k),φ_(k)),a ₂(θ_(k),φ_(k)), . . . ,a_(M)(θ_(k),φ_(k))]^(T) ∈C ^(M×1)  (1)

If K user signals s_(k)(t), k=0, 1, . . . K−1, arrive from (θ₁, φ₂),(θ₂, φ₂), . . . , and (θ_(K), φ_(K)) respectively, the array outputvector can be expressed as a linear combination of the K incidentwaveforms and noise as below:

$\begin{matrix}{{y(t)} = {{{\sum\limits_{k = 0}^{K - 1}{{a\left( {\theta_{k},\varphi_{k}} \right)}{s_{k}(t)}}} + {I(t)} + {n(t)}} = {{{{As}(t)} + {I(t)} + {n(t)}}\mspace{31mu} \in C^{M \times 1}}}} & (2)\end{matrix}$where

A=[a(θ₁,φ₁)a(θ₂,φ₂) . . . a(θ_(K),φ_(K))]  (3)

is the array manifold that consists of K steering vectors, and

s(t)=[s ₁(t)s ₂(t) . . . s _(K)(t)]^(T)  (4)

is the vector of signal waveforms, and I(t) is the vector of cochannelinterference that may include ancillary terrestrial component (ATC)interference, and n(t) is the additive complex Gaussian noise vector. Inone embodiment, for a known location of the h user at (θ_(k), φ_(k)), toform a beam toward the k^(th) user with the MMSE criterion, thebeamformer may have the weights given by

w=R _(y) ⁻¹ a(θ_(k),φ_(k))  (5)

where

R _(y) =E{yy ^(H)}  (6)

is the antenna array co-variance matrix.

In another embodiment, for a known waveform of the k^(th) user s_(k)(t),to form a beam toward the k^(th) user with the MMSE criterion, thebeamformer may have the weights given by

w=R _(y) ⁻¹ r _(ys)  (7)

where

r _(ys) =E{ys _(k)*}  (8)

is the correlation vector between the received vector and referencesignal, which essentially is the estimated steering vector for thek^(th) user.

2.2 Forward Link Method

Forward link beamforming is different from return link beamformingbecause the transmit antenna elements and receive antenna elements havedifferent feed patterns (as a function of frequency) for an FDD systemsuch as the one in satellite. Also, unlike the return link where thereceived array co-variance matrix R_(y) can be estimated from thereceived array vector signal y(t), the forward link array co-variancematrix obviously does not exist. In the case of the forward link, a“virtual transmit array co-variance matrix” is introduced as a part offorward link beamforming method.

As the adaptive scheduler at S-BSS has all information about thelocations of all the users, and power and bandwidth allocation for allthe users, a “virtual transmit array co-variance matrix” can beconstructed based on this information. In some embodiments, the “virtualtransmit array co-variance matrix” can be constructed based on estimatedspatial steering vectors. Assume that scheduler allocates total of Kcochannel users whose carrier frequency has overlaid one another, andthe K cochannel user locations are at (θ₁, φ₁), (θ₂, φ₂), . . . , and(θ_(K), φ_(K)) respectively. In addition, the corresponding allocatedtransmit power spectrum densities for the K cochannel users are p₁, p₂,. . . , p_(K) respectively. Now let's define a cochannel transmit arrayco-variance matrix as the following

R _(T) =A _(T)(θ,φ)PA _(T) ^(H)(θ,φ)  (9)

where

$\begin{matrix}{{A_{T}\left( {\theta,\varphi} \right)} = {\left\lbrack {{a_{T}\left( {\theta_{1},\varphi_{1}} \right)}{a_{T}\left( {\theta_{2},\varphi_{2}} \right)}\mspace{14mu}\ldots\mspace{20mu}{a_{T}\left( {\theta_{K},\varphi_{K}} \right)}} \right\rbrack = {\begin{bmatrix}{a_{1}\left( {\theta_{1},\varphi_{1}} \right)} & {a_{1}\left( {\theta_{2},\varphi_{2}} \right)} & \ldots & {a_{1}\left( {\theta_{K},\varphi_{K}} \right)} \\{a_{2}\left( {\theta_{1},\varphi_{1}} \right)} & {a_{2}\left( {\theta_{2},\varphi_{2}} \right)} & \ldots & {a_{2}\left( {\theta_{K},\varphi_{K}} \right)} \\\vdots & \vdots & \ldots & \vdots \\{a_{M}\left( {\theta_{1},\varphi_{1}} \right)} & {a_{M}\left( {\theta_{2},\varphi_{2}} \right)} & \ldots & {a_{M}\left( {\theta_{K},\varphi_{K}} \right)}\end{bmatrix}\mspace{34mu} \in C^{M \times K}}}} & (10)\end{matrix}$

with a_(m)(θ_(k),φ_(k)) being the m^(th) transmit feed element complexresponse at θ_(k) and

$\begin{matrix}{P = {{{diag}\left\{ {p_{1},p_{2},\ldots\mspace{14mu},P_{K}} \right\}} = {\begin{bmatrix}p_{1} & 0 & \ldots & 0 \\0 & p_{2} & 0 & 0 \\\vdots & 0 & \ddots & \vdots \\0 & 0 & \ldots & p_{K}\end{bmatrix}\mspace{31mu} \in R^{K \times K}}}} & (11)\end{matrix}$

The matrix R_(T) formed in Equation (9) is called as “virtual transmitarray co-variance matrix”. With R_(T) being defined, the forward linkbeamforming weight for the k^(th) user at location (θ_(k), φ_(k)) isgiven by

w=R _(T) ⁻¹ a _(T)(θ_(k),φ_(k))  (12)

where

a _(T)(θ_(k),φ_(k))=[a ₁(θ_(k),φ_(k)),a ₂(θ_(k),φ_(k)), . . . a_(M)(θ_(k),φ_(k))]^(T) ∈C ^(M×1)  (13)

is transmit steering vector toward the desired k^(th) user.

2.3 Simulation Examples

The performance of the new user beamforming system versus aconventional, fixed (non-adaptive), spot-beamforming system has beeninvestigated with simulations of an L-band GEO satellite. The twosystems were assumed to have the same number and spatial distribution ofusers. FIG. 8 illustrates an example of return link (RL) beam contoursproduced with embodiments of the user beamforming system presentedherein, while FIG. 9 illustrates an example of return link (RL) beamcontours with the conventional, fixed spot-beamforming system. Asillustrated in FIG. 8, that the user beam 802 puts a null on eachcochannel user 804 while trying to maximize the gain to the desired user806.

To quantify the performance, Monte-Carlo simulations were conducted toprovide the CDF (cumulative distribution function) ofE_(s)/(I_(o)+N_(o)) among all users for the two systems (adaptive andfixed). MMSE (Minimum Mean Squared Error) was the optimization criterionused for adaptive beamforming and LCMV (Linearly Constrained MinimumVariance) was the optimization criterion used for designing the fixedbeams. The simulations show that the new system offers significantlybetter performance than the legacy system for both return link (RL) andforward link (FL), as shown in FIG. 10 and FIG. 11, respectively. Theimprovement of user's SINR leads to improvement of the system capacity(measured as network-wide aggregate throughput). FIG. 15 (chart 1500)further illustrates the performance improvements of a user beam systemover a conventional fixed spot beam system.

3. Bootstrapping of a UE in an Individual-User Optimized AdaptiveBeamforming System

When a UE tries to initially join the network, there is no user beam.This section presents a method to enable a UE to initially join thenetwork and establish a user beam. We first introduce the concepts ofquiescent state beams and steady state beams. The quiescent state beamsare the ones used by the S-BSS before a user beam is established tobroadcast synchronization signals, reference signals, and systeminformation (SI) that provides essential information for the UE tooperate in the network. The steady state beams are the adaptivelyformed, individual-user-optimized beams generated by the S-BSS in theconnected state. We refer to the latter as “user beams.” The user beamshape adapts to the distribution of the ensemble of all cochannel UEs inthe footprint of the satellite, while attempting to maximize the SNIR ofthe desired UE. FIG. 12 illustrates the S-BSS new beam concept anddefinitions. The fixed regional beams 1202 are used in the quiescentstate, and the user beams 1204 are used in the steady state (i.e.,connected state). The fixed regional beams 1202 may initially serve theusers using a traditional, 3-color frequency reuse, illustrated as anexample in FIG. 12. The use of a frequency reuse factor of 3 is cited asan example and is neither essential nor prescriptive. The fixed regionalbeam may be optimized to achieve a desired shape, such as minimumin-beam gain and minimum out-of-beam rejection at selected points in thebeam's look angle, using algorithms such as the fixed LCMV. The beamscould be the actual beams for a legacy system.

The bootstrap procedure for S-BSS system with adaptive user beams may beair interface dependent. FIG. 13 illustrates one example embodiment ofan adaptive user beam startup procedure 1300, described in terms of anLTE satellite air interface for a space-based network (SBN) 1302 and auser equipment (UE) 1304.

Step 1—Fixed regional DL beams broadcast system information (SI), whichis common to all beams, plus synchronization signals (SS) and referencesignals (RS), which are unique to each of the fixed beams, as sent tothe UE 1304.

Step 2—The UE 1304 scans all the frequency bands supported by the UE1304, and finds the strongest beam as the beam selection candidate.

Step 3—The UE 1304 searches for SS to perform time and frequencysynchronizations.

Step 4—The UE 1304 synchronizes to the SS to perform beam identificationand initial frame synchronization.

Step 5—The UE 1304 performs system information (SI) acquisition ondownlink physical broadcast channel (PBCH), which may include systembandwidth, PRACH (physical random access channel) configurationinformation.

Step 6—The UE 1304 estimates the uplink timing advance by using its GPSlocation information and the Satellite location information, whichimproves overall system latency and efficiency relative to present 3GPPmethods. However, a suitable adaptation of the latter may also be used.

Step 7—The UE 1304 performs RS based reference signal received power(RSRP) measurement and send a PRACH preamble with appropriate PRACHpower level to request access to the SBN 1302 with the estimated timingadvance.

Step 8—A Satellite Base Station Subsystem, through the correspondingFixed regional UL beam, detects PRACH preamble and send back randomaccess response (RAR) which may contain UL timing command (if any timingadjustment is needed) and scheduling information pointing to radioresources that the UE 1304 can use to transmit a request to connect.

Step 9—The UE 1304 transmits a request to connect which contains itsidentity and location information as part of a Radio Resource Control(RRC) layer message.

Step 10—The SBN 1302 transmits a connection setup/resume message andcontention resolution data that resolves any contention due to possiblemultiple UEs transmitting the same preamble in Step 7.

Step 11—The UE 1304 replies with a connection setup/resume completemessage to terminate the random access procedure and complete thetransition to connected state.

Step 12—The SBN 1302 forms a user UL beam (receive beam) for the UE 1304based on the UE locations or the UE reference pilot signal and networkradio resource scheduling information, and switches the receive beamfrom the fixed UL regional beam to the user-based UL beam for the ULdata packet.

Step 13—The SBN 1302 forms a user DL beam (transmit beam) for the UE1304 based on the UE locations or the UE reference pilot and networkradio resource scheduling information, and switches the transmit beamfrom the fixed DL regional beam to the user-based DL beam for the DLdata packet.

Step 14—The SBN 1302 completes DL/UL data packet in the connected state.

Step 15—The SBN 1302 transmits RRC connection release on PDSCH.

Step 16—UE 1304 responds to acknowledge RRC connection release on PUSCHRLC.

4. Mobility Management for User Based Beamforming Space-Based Network(SBN)

In idle mode, when the MME (mobile management entity) in the corenetwork needs to page a UE, it informs the involved user beam entity inthe S-BSS, so that the paging can be transmitted through the user beam.In that case, the MME has been keeping UE history information since anearlier session in the user beam. This assumes that the device isstationary since its last access to the network. However, if the devicemoves around when in idle mode, the MME may not have adequateinformation about the coverage situation changes. In this case, somelevel of MO (mobile originated) traffic may be used to assist the MME inkeep track of the UE, and thus to improve the DL reachability for thedevice. For example, the network can track the device by usingdevice-triggered location updates.

In connected mode, a UE keeps updating its location information so thatthe SBN network can update the user beam weight adaptively to allcochannel user situations. Meanwhile the SBN can determine whether theUE is still in the same “regional beam zone” from the latest locationupdate. If the UE is moving out of the current zone and into aneighboring “regional beam zone”, the network starts the handoverprocess by informing the UE new frequency and/or time schedulinginformation and updating the user beam with new beam weight accordinglysince the beam weight set is dependent on the frequency allocation. Thehandover to the new user beam should be seamless to the user as the userbeam still maximizes SINR toward the same desired user, only adaptivelyto the new cochannel user situations.

In the foregoing specification, specific embodiments have beendescribed. However, one of ordinary skill in the art appreciates thatvarious modifications and changes can be made without departing from thescope of the invention as set forth in the claims below. Accordingly,the specification and figures are to be regarded in an illustrativerather than a restrictive sense, and all such modifications are intendedto be included within the scope of present teachings.

Various features and advantages of some embodiments are set forth in thefollowing claims.

What is claimed is:
 1. A method of beamforming for a satellite system,the method comprising: generating, with a ground based beamformer, acustomized user beam for a user equipment, the user equipment having alocation and transmitting a known pilot signal; wherein the ground basedbeamformer interfaces with a plurality of satellite antennas on afeederlink side and a plurality of beam ports on a satellite basestation subsystem side; wherein the ground based beamformer is operatedin a transparent mode, whereby individual satellite antennas areconnected to individual beam ports.
 2. The method of claim 1, whereinoperating the ground based beamformer in a transparent mode includesconnecting one of the plurality of satellite antennas to one of theplurality of beam ports by using a complex weight vector.
 3. The methodof claim 2, further comprising: setting a real part of a first weightelement of the complex weight vector to a non-zero value; setting animaginary part of the first weight element to zero; and for each of aplurality of additional weight elements of the complex weight vector,setting a real part of the additional weight element to zero, andsetting an imaginary part of the additional weight element to zero. 4.The method of claim 3, further comprising: selecting the first weightelement based on a particular feed element connected to the satellitebase station subsystem.
 5. The method of claim 1, wherein generating acustomized user beam includes generating a customized user beam for areturn link of the satellite system.
 6. The method of claim 5, whereingenerating a customized user beam for a return link includes maximizinga signal to noise and interference ratio of a signal received from theindividual user equipment.
 7. The method of claim 5, further comprising:receiving, by the ground-based beamformer via the plurality of satelliteantennas, complex baseband signals received from an antenna array of asatellite of the satellite system; wherein generating a customized userbeam for a return link includes analyzing the complex baseband signals,and maximizing the signal to noise and interference ratio of the signalreceived from the individual user equipment.
 8. The method of claim 1,wherein generating a customized user beam includes generating acustomized user beam for a forward link by constructing a virtualtransmit array co-variance matrix based on the locations, power, andbandwidth allocations of all active users, and forming a user beam thatmaximizes the gain towards the desired user while minimizing the gainstowards all other active co-channel users.
 9. The method of claim 8,further comprising: transmitting, with the satellite base stationsubsystem, complex baseband signals to individual elements of an antennaarray on a satellite.
 10. The method of claim 9, further comprising:passing the complex baseband signals through the ground-basedbeamformer.
 11. A system for beamforming in a satellite communicationnetwork, the system comprising: a electronic processor communicativelycoupled to a satellite system and configured to generate, with aground-based beamformer that interfaces with a plurality of satelliteantennas on a feederlink side and a plurality of beam ports on asatellite base station subsystem side, a customized user beam for theuser equipment, the user equipment having a location and transmitting aknown pilot signal; and operate the ground based beamformer in atransparent mode, whereby individual satellite antennas are connected toindividual beam ports.
 12. The system of claim 11, wherein theelectronic processor is configured to: operate the beamformer in atransparent mode by connecting one of the plurality of satelliteantennas to one of the plurality of beam ports by using a complex weightvector.
 13. The system of claim 12, wherein the electronic processor isconfigured to: set a real part of a first weight element of the complexweight vector to a non-zero value; set an imaginary part of the firstweight element to zero; and for each of a plurality of additional weightelements of the complex weight vector, set a real part of the additionalweight element to zero, and set an imaginary part of the additionalweight element to zero.
 14. The system of claim 13, wherein theelectronic processor is configured to: select the first weight elementbased on a particular feed element connected to the satellite basestation subsystem.
 15. The system of claim 11, wherein the electronicprocessor is configured to: generate the customized user beam for areturn link of the satellite system.
 16. The system of claim 15, whereinthe electronic processor is configured to: generate the customized userbeam by maximizing a signal to noise and interference ratio of a signalreceived from the individual user equipment.
 17. The system of claim 15,wherein the electronic processor is configured to: receive, via theplurality of satellite antennas, complex baseband signals received froman antenna array of a satellite of the satellite system; and generate acustomized user beam for a return link by analyzing the complex basebandsignals, and maximizing the signal to noise and interference ratio ofthe signal received from the individual user equipment.
 18. The systemof claim 11, wherein the electronic processor is configured to generatethe customized user beam for a forward link by constructing a virtualtransmit array co-variance matrix based on the locations, power, andground based, and forming a user beam that maximizes the gain towardsthe desired user while minimizing the gains towards all other activeco-channel users.
 19. The system of claim 18, wherein the electronicprocessor is configured to: transmit, with the satellite base stationsubsystem, complex baseband signals to individual elements of an antennaarray on a satellite by passing the complex baseband signals through theground-based beamformer.
 20. The system of claim 19, wherein thegeneration of the customized beam is integrated into the satellite basestation subsystem.